期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

基于粒子滤波的约束目标被动跟踪研究 被引量：3

Constraint Target Passive Tracking Based on Particle Filter
下载PDF
导出
摘要 为提高约束条件下的二维机动目标被动跟踪性能,提出了一种约束下的粒子滤波方法(CPF).使用转弯率概念建立了被动跟踪模型,阐述了非线性粒子滤波的基本过程;通过设定地域和机动性能约束条件,抛弃约束外粒子,并对粒子分布和权重进行调整;利用CPF进行了目标跟踪仿真实验,与无约束的粒子滤波跟踪进行了对比,分析了轨迹跟踪性能,比较了跟踪误差.仿真结果表明,CPF能够稳定跟踪,并且具有更高的跟踪精度. To improve the passive tracking performance of 2D maneuvering target, a new constraint particle filter （CPF） is proposed. The passive tracking dynamics is modeled by the turn rate, and the basic steps of the nonlinear particle filter are discussed. According to constraint conditions including the terrain data and the maneuvering capability of the target, outrange particles are discarded during prediction and update steps, and the distribution and the weight of particles are adjusted. The performance and the RMSE are analyzed by comparison simulations with the unconstraint particle filter （UPF）. The results show that the CPF is able to track the target stably and is more accurate than the UPF.
作者 薛锋 刘忠 石章松
机构地区 海军工程大学电子工程学院
出处 《武汉理工大学学报（交通科学与工程版）》 2007年第1期43-45,52,共4页 Journal of Wuhan University of Technology（Transportation Science & Engineering）
基金 国防预研项目资助(批准号:413060201)
关键词 粒子滤波 机动目标 被动跟踪 约束条件 passive tracking particle filter constraint condition maneuvering target
分类号 TN953 [电子电信—信号与信息处理]
  • 相关文献

参考文献6

二级参考文献9

  • 1夏佩伦.纯方位目标跟踪系统分析[J].舰船论证参考,1991,(1):57-64.
  • 2刘忠 周丰 吴玲.一种多方位一距离目标定位的最小二乘伴随估计器[J].海军工程学院学报,1999,11(4):13-16.
  • 3Blackman S S, Popoli R. Design and analysis of modern tracking systems. Boston: Artech Hourse.1999
  • 4Lee M S, Kim Y H. New data association method for automotive radar tracking. IEE Proc.-Radar, Sonar, Navig.2001,148 (5): 296～301
  • 5Song Taek L, Speyer Jason L. A Stochastic Analysis of a Modified Gain Extended Kalman Filter with Applications to Estimation with Bearings only Measurements[J]. IEEE Trans. on Automatic Control, 1985, AC-30(10):940-949.
  • 6Tremois O, Le Cadre P. Optimal Observer Trajectory in Bearings-only Tracking for Manoeuvring Sources[J]. IEE Proc. Radar, Sonar Navig., 1999,146(1): 31-39.
  • 7Passerieux J M, Van Cappel D. Optimal Observer Maneuver for Bearings-only Tracking[J]. IEEE Trans. on Aerospace and Electronic Systems, 1998, 34(3): 777-787.
  • 8National Academies. Technology for the United States Navy and Marine Corps, 2000-2035 Becoming a 21st Century Force. Volume1～9.Washington: The National Academy Press, 1997.
  • 9党宏社,韩崇昭,段战胜.一种基于模糊量相似度测量的模糊数据关联方法[J].武汉理工大学学报（交通科学与工程版）,2003,27(1):11-14. 被引量：13

共引文献18

同被引文献16

  • 1Gordon N J, Salmond D J,Smith A F M. A novel approach to nonlinear/non-Gaussian Bayesian state estimation[J]. IEE Proceedings-F, 1993,140 (2) : 107 - 113.
  • 2Arulampalam S, Maskell S. A tutorial on particle filters for no-line/no-Gaussian Bayesian tracking [J]. IEEE Transactions of Signal Processing, 2002, 50 (2): 174- 188.
  • 3AndrieuC, Freitas N D. Doucet A, et al ,An introduction to MCMC for machine learning[J]. Machine Learning, 2003, 50 (1/2): 5-43.
  • 4Jayesh H K, Peter M D. Gaussian sum particle filtering[J]. IEEE Transactions on Signal Processing, 200a, 51 (10) : 2602-2612.
  • 5Djuric P M, Kotecha J H, et al. Particle filtering[J]. IEEE Signal Processing Magazine, 2003, 20 (5): 19 -38.
  • 6HUE C, le CADRE J P. Sequential Monte Carlo methods for multiple target tracking and data fusion [ J ]. IEEE Transactions on Signal Processing,2002,50(2) :309-325.
  • 7KARLSSON R, GUSTAFSON F. Recursive Bayesian estimation: bearing-only application [ J ]. IEEE Proc Radar Sonar Naving,2005,152 (2) : 305-314.
  • 8REID D. An algorithm for tracking multiple targets [ J ]. IEEE Trans Automat Contr, 1979,24(6) :84-90.
  • 9SCHULZ D. Tracking muhiple moving targets with a mobile robot using particle fihers and statistical data association[ C ]//IEEE Int Conf Robotics Automat Seoul, Korea, 2001 : 1665-1670.
  • 10DOUCET A, GORDON N. Particle filter for state estimation of jump Markov linear systems [ J ]. IEEE Trans on Signal Processing,2001,49 ( 3 ) : 613-624.

引证文献3

二级引证文献3

武汉理工大学学报（交通科学与工程版）
2007年 第1期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部